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This paper presents an approach to more efficient partial order reduction for model checking concurrent systems. This approach utilizes a compositional reachability analysis to generate over-approximate local state transition models for all…

Software Engineering · Computer Science 2020-05-01 Hao Zheng , Yingying Zhang , Chris Myers

State-space reduction techniques, used primarily in model-checkers, all rely on the idea that some actions are independent, hence could be taken in any (respective) order while put in parallel, without changing the semantics. It is thus not…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-04-03 Lisbeth Fajstrup , Eric Goubault , Emmanuel Haucourt , Samuel Mimram , Martin Raussen

Problems arise when using reward functions to capture dependencies between sequential time-constrained goal states because the state-space must be prohibitively expanded to accommodate a history of successfully achieved sub-goals. Also,…

Artificial Intelligence · Computer Science 2019-02-13 Thomas J. Ringstrom , Paul R. Schrater

This paper presents a range of quantitative extensions for the temporal logic CTL. We enhance temporal modalities with the ability to constrain the number of states satisfying certain sub-formulas along paths. By selecting the combinations…

Logic in Computer Science · Computer Science 2015-07-01 François Laroussinie , Antoine Meyer , Eudes Petonnet

Timed Concurrent State Machines are an application of Alur's Timed Automata concept to coincidence-based (rather than interleaving) CSM modeling technique. TCSM support the idea of testing automata, allowing to specify time properties…

Logic in Computer Science · Computer Science 2017-10-24 Wiktor B. Daszczuk

Since the introduction of Alternating-time Temporal Logic (ATL), many logics have been proposed to reason about different strategic capabilities of the agents of a system. In particular, some logics have been designed to reason about the…

Logic in Computer Science · Computer Science 2017-09-08 Simon Busard , Charles Pecheur

Recent State Space Models (SSMs) such as S4, S5, and Mamba have shown remarkable computational benefits in long-range temporal dependency modeling. However, in many sequence modeling problems, the underlying process is inherently modular…

Artificial Intelligence · Computer Science 2024-12-03 Jindong Jiang , Fei Deng , Gautam Singh , Minseung Lee , Sungjin Ahn

Continuous-time reinforcement learning (CTRL) provides a natural framework for sequential decision-making in dynamic environments where interactions evolve continuously over time. While CTRL has shown growing empirical success, its ability…

Machine Learning · Computer Science 2025-12-04 Runze Zhao , Yue Yu , Ruhan Wang , Chunfeng Huang , Dongruo Zhou

Autonomous control systems use various sensors to decrease the amount of uncertainty under which they operate. While providing partial observation of the current state of the system, sensors require resources such as energy, time and…

Logic in Computer Science · Computer Science 2016-02-29 Eva Tesarova , Maria Svorenova , Jiri Barnat , Ivana Cerna

This paper revisits the classical notion of sampling in the setting of real-time temporal logics for the modeling and analysis of systems. The relationship between the satisfiability of Metric Temporal Logic (MTL) formulas over…

Logic in Computer Science · Computer Science 2015-03-13 Carlo A. Furia , Matteo Rossi

Formal control of cyber-physical systems allows for synthesis of control strategies from rich specifications such as temporal logics. However, the classes of systems that the formal approaches can be applied to is limited due to the…

Logic in Computer Science · Computer Science 2019-09-04 Irmak Saglam , Ebru Aydin Gol

The use of spatio-temporal logics in control is motivated by the need to impose complex spatial and temporal behavior on dynamical systems, and to control these systems accordingly. Synthesizing correct-by-design control laws is a…

Formal Languages and Automata Theory · Computer Science 2020-03-26 Lars Lindemann , Dimos V. Dimarogonas

This paper presents control strategies based on time-varying convergent higher order control barrier functions for a class of leader-follower multi-agent systems under signal temporal logic (STL) tasks. Each agent is assigned a local STL…

Systems and Control · Electrical Eng. & Systems 2021-10-12 Maryam Sharifi , Dimos V. Dimarogonas

This paper presents algorithms for identifying and reducing a dedicated set of controllable transition rates of a state-labelled continuous-time Markov chain model. The purpose of the reduction is to make states to satisfy a given…

Systems and Control · Computer Science 2016-08-03 Bharath Siva Kumar Tati , Markus Siegle

We investigate the expressive power of state space models (SSM), which have recently emerged as a potential alternative to transformer architectures in large language models. Building on recent work, we analyse SSM expressiveness through…

Logic in Computer Science · Computer Science 2026-01-28 Eric Alsmann , Lowejatan Noori , Martin Lange

Prior work on automatic control synthesis for cyber-physical systems under logical constraints has primarily focused on environmental disturbances or modeling uncertainties, however, the impact of deliberate and malicious attacks has been…

Systems and Control · Electrical Eng. & Systems 2019-07-25 Luyao Niu , Andrew Clark

We introduce a temporal logic to reason on global applications in an asynchronous setting. First, we define the Distributed States Logic (DSL), a modal logic for localities that embeds the local theories of each component into a theory of…

Logic in Computer Science · Computer Science 2016-08-31 Carlo Montangero , Laura Semini

We propose algorithms for performing model checking and control synthesis for discrete-time uncertain systems under linear temporal logic (LTL) specifications. We construct temporal logic trees (TLT) from LTL formulae via reachability…

Systems and Control · Electrical Eng. & Systems 2020-07-07 Yulong Gao , Alessandro Abate , Frank J. Jiang , Mirco Giacobbe , Lihua Xie , Karl H. Johansson

Two moment-matching methods for model reduction of linear switched systems (LSSs) are presented. The methods are similar to the Krylov subspace methods used for moment matching for linear systems. The more general one of the two methods, is…

Systems and Control · Computer Science 2016-11-15 Mert Bastug , Mihaly Petreczky , Rafael Wisniewski , John Leth

Reinforcement Learning (RL) based methods have seen their paramount successes in solving serial decision-making and control problems in recent years. For conventional RL formulations, Markov Decision Process (MDP) and state-action-value…

Machine Learning · Computer Science 2020-06-09 Ziyao Zhang , Liang Ma , Kin K. Leung , Konstantinos Poularakis , Mudhakar Srivatsa
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